Related art systems often monitor the condition of photovoltaic (PV) devices or systems based almost entirely on the energy that they produce, sometimes normalized by the systems' expected output based on the solar resource and the ambient temperature. This type of monitoring can identify major problems, but only after they have already had a major effect on the energy output. This poor sensitivity leads to high uncertainty in the future output of a PV system. Once a drop in yield is detected, a reactive, expensive chain of manual troubleshooting steps is initiated to identify and remediate the problem.
Further, occasional and superficial maintenance visits may fail to detect incipient problems before they lead to lost production and safety hazards. These increase the investment risk in utility-scale solar electricity, resulting in higher financing costs. If and when reduced energy production is detected, information about the specific cause can only be found using costly and labor-intensive manual techniques, adding to operations and maintenance cost and reducing yield until the problem is addressed. In addition, there is emerging pressure to improve monitoring and periodic inspections of PV systems, and to identify causes and trends in failures, so that performance and safety problems can be promptly resolved through maintenance or warranty claims.